云计算中隐私需求的建模与验证框架

128 浏览量更新于2024-08-30 收藏 254KB PDF 举报

云计算作为一种革命性的计算模式，其动态异构特性在跨层服务组合中带来了前所未有的效率，但同时也对传统的安全、信任和隐私机制提出了新的挑战。传统的数据加密和访问控制策略可能不足以应对云环境中日益复杂的隐私需求。因此，准确描述和验证云服务的隐私需求与实际系统实践之间的兼容性成为亟待解决的问题。本文主要关注"云计算中的隐私需求建模和验证"这一研究领域。作者Jin Wang，来自南京航空航天大学计算机科学技术学院，探讨了如何开发一套适应云计算新范式的解决方案，以支持模型检查一致性、蕴含关系以及与隐私需求和云应用隐私模型的符合性。该框架旨在确保云服务提供商能够在满足用户期望的同时，保护个人数据隐私。文章首先概述了问题背景，指出当前研究中面临的主要挑战，包括如何在动态变化的服务环境中构建稳定且可验证的隐私模型。作者提出了一个支持形式化定义的隐私需求和云应用隐私模型的验证框架，通过这个框架，可以精确地识别和评估系统的隐私保护能力。为了解决这些问题，文中可能探讨了多种方法，如抽象建模技术、机器学习驱动的隐私分析、协议设计以及自动化验证工具的使用。此外，论文可能还涉及了现有的隐私保护标准和最佳实践，以及它们在云计算环境中的适用性和局限性。在研究方法部分，作者可能会介绍实验设计，通过对比不同的建模和验证策略，评估其在真实或模拟云环境中的性能和效果。同时，作者可能会引用相关领域的博士论文，深入分析其研究成果，并对其解决方案的有效性和实用性进行评估。关键词包括"云计算"、"隐私需求建模"、"模型验证"、"云应用隐私模型"和"形式化方法"，这些关键词反映了论文的核心议题和研究重点。这篇研究论文在云计算的大背景下，对隐私需求的精确描述和验证进行了深入研究，为云服务提供商提供了有效的隐私保障策略，并对当前和未来的研究方向提供了有价值的见解。通过阅读这篇论文，读者将能了解到如何在不断发展的云计算世界中，更好地平衡数据利用与用户隐私保护的关系。

Privacy Requirement Modeling and Verification in

Cloud Computing

Jin, Wang

College of Computer Science and Technology

Nanjing University of Aeronautics and Astronautics

Nanjing, China

woodenwang55@hotmail.com

Abstract—Cloud computing, the architecture which shares

dynamic heterogeneous characteristics in the cross-layer service

composition, has affected traditional security, trust and privacy

mechanisms which are mainly based on data encryption and

access control. Approaches that can support accurate privacy

requirement description and verifiable compliance between the

privacy requirement and system practice need to be developed to

fit this new paradigm. To tackle the issues of privacy

requirement modeling and verification in cloud computing, a

framework that supports model checking consistency, entailment

and compliance with the formal definition of privacy

requirements and privacy model of cloud application is proposed.

This paper provides an overview of the scientific research

problem, approaches to solve the problem and ways to evaluate

the solution found by the research related PhD thesis.

Keywords—Cloud computing, privacy requirement, model

checking, formal model

PROBLEM

Scalability, on-demand access and network-based message

delivery are three core characteristics of cloud computing [1].

As a scalable and hierarchical distributed collaboration

paradigm, cloud computing is envisioned as an XaaS (X As a

Service) architecture, combined with the advantage of reducing

cost by sharing computing and storage resources [2]. Although

there is a large push towards cloud computing, security and

privacy are the major challenges which inhibit the cloud

computing’s wide acceptance in practice. A survey conducted

by the US Government Accountability Office (GAO) states

that “22 of 24 major federal agencies reported that they were

either concerned or very concerned about the potential

information security and privacy risks associated with cloud

computing” [3]. Different from the traditional architecture in

which users have full control of their privacy data, the internal

operations of cloud computing software systems are usually

transparent to the users and once the privacy data of the users

are collected, they will lose control over it.

The essence of privacy protection in cloud computing is the

rights and obligations of individuals and service providers with

respect to the collection, use, disclosure, and retention of PII

(Personally Identifiable Information) [4,5]. Providing verifiable

mechanism in design phase to ensure that the practice of

software is compliant with the privacy requirement is one of

the most important principles in privacy related standards and

regulations such as OECD [6] and ISO29100 [7]. The issues

appearing in this principle are manifold.

Firstly, we need an approach to precisely describe the

privacy requirement. On the one hand, due to the ambiguous

and inconsistent essence, natural language is essentially

unusable to depict a user concerned privacy

requirement. On

the other hand, directly using a specification language, such as

Linear Temporal Logic (LTL) and Description Logics (DL), is

too

complicated

to be implemented by the requirements

analysts and system designers. Therefore, we must establish

one privacy requirement description method that can make a

balance between the expressiveness and the applicability.

Secondly, considering the multi-participant and outsource

nature of cloud computing, we must guarantee there is no

conflict among different participants which means the privacy

requirement among different participants should be

consistent with each other.

Thirdly, some laws and regulations in different

application contexts, such as the Children Online Privacy

Protection Act (COPPA), the Health Information Portability

and Accountability Act (HIPAA) and the Gramm–Leach–

Bliley Act (GLBA), are proposed to enforce the privacy

requirements of each participant and we must make sure the

privacy requirements entail certain privacy regulations and

laws.

Finally, we need to verify the compliance between the

cloud computing system practice and requirements. To

support the verification, a formal model of privacy

requirements and the specified cloud computing privacy model

are needed. Moreover, to overcome the space explosion

dilemma in traditional model checking, there should be some

reduction method to make our verification represent real-life

systems and not just toy examples.

II. RELATED

WORK

A. Privacy Requirement Description

Current privacy policy definition methods can be classified

into four categories, access control model based on

RBAC(Role-Based Access Control), access control models

using Markup Language, Semantic-web policy frameworks

using description logic and declarative language with formal

semantics.

下载后可阅读完整内容，剩余4页未读，立即下载

weixin_38599712

粉丝: 8
资源: 860

云计算中隐私需求的建模与验证框架

基于隐私的云计算SLA违规检测模型.pdf

移动云计算中证书游戏的演化信任方案

工业互联网-云计算技术.pptx

云计算安全架构机制与模型评价

云计算隐私保护：5A问责制建模与安全策略

移动云计算中的证书游戏信任演进策略

算法在云计算中的应用：揭秘算法在云计算平台中的关键作用

探索Matlab mat文件在云计算中的潜力：存储和管理数据更灵活

Python random模块与云计算的邂逅：随机数在云计算中的奇妙应用

状态机在云计算中的创新用法：探索其在云平台中的应用

最新资源